仿生光纤触觉传感，让机器人像人一样感知触摸。
Towards Artificial Nerves: Biomimetic Optical-Fiber Tactile Sensing for Robots
- 用软肤上的机械钉配光纤，模拟人体触觉神经结构。
- 可高精度识别接触位置、大小和形状，无需深度学习。
- 适合需要可解释触觉的机器人操控与安全交互场景。
机器人系统日益需要接近人类皮肤适应性与分辨率的触觉感知，以实现灵巧操作与安全交互。OptiTac 是一种仿生触觉传感器，通过将柔软皮肤上的每个机械钉与一根光学纤维（作为人工神经）配对，模仿人体触觉感受器到神经的架构。该设计展示了一种将触觉信息从传感表面远距离传输的同时保持高空间分辨率的架构原理，为未来机器人系统的分布式触觉感知提供了可行路径。通过将触觉信号视为图像，采用简单的分析方法而非黑箱深度学习模型，即可推断接触的位置、尺寸和形状，实现可解释且可扩展的触觉智能。本工作表明，生物进化原理可指导人工神经系统的开发，为下一代机器人平台实现类人触觉感知提供新路径。更广泛而言，OptiTac 建立了受人工神经启发的可解释触觉感知框架，并为未来的分布式触觉系统提供了可扩展方案。
原文摘要 · Abstract (English)
Robotic systems increasingly demand tactile sensing that approaches the adaptability and resolution of human skin to enable dexterous manipulation and safe interaction. OptiTac is a biomimetic tactile sensor that emulates the mechanoreceptor-to-nerve architecture of human touch by pairing each mechanical pin on a soft skin with an optical fiber acting as an artificial nerve. This design demonstrates an architectural principle for routing tactile information away from the sensing surface while preserving high spatial resolution, establishing a practical route toward distributed tactile sensing in future robotic systems. By treating tactile signals as images, simple analytical methods, rather than opaque deep-learning models, are used to infer contact location, size, and shape, providing interpretable and scalable tactile intelligence. This work demonstrates how evolutionary principles from biology can guide the development of artificial nerve systems for robots, offering a pathway toward human-like tactile perception in next-generation robotic platforms. More broadly, OptiTac establishes an artificial nerve-inspired sensing framework for interpretable robotic touch and a scalable route toward future distributed tactile systems.
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